The book deals with the task of determining the state vector of a linear dynamic system from the measurable output variables. This problem is initially considered as a deterministic observation task, meaning that it does not explicitly take into account random disturbances and measurement errors. By incorporating stochastic initial values, disturbance variables, and measurement errors, the Kalman-Bucy filtering is presented as the optimal generalization of Gaussian least squares estimation.